{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a8833c8e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from data_processing import get_from_file\n",
    "from word_cloud import display_word_cloud\n",
    "from topic_analysis import do_lda, print_top_words\n",
    "from clustering import do_kmeans, visualize_kmeans\n",
    "from classificiation import do_svm\n",
    "import datetime as dt\n",
    "from collections import Counter\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import joblib\n",
    "\n",
    "# period\n",
    "begin_date = dt.datetime(2022, 2, 24)\n",
    "end_date = dt.datetime(2022, 4, 30)\n",
    "period = \"2022.02.24-2022.04.30\"\n",
    "lang = \"en\"\n",
    "\n",
    "# tokenize\n",
    "weibo_data_path = \"data/weibo_2022.02.01-2022.11.30.jsonl\"\n",
    "twitter_data_path = \"data/twitter_2022.02.24-2022.11.26.jsonl\"\n",
    "processed_data_path = \"data/%s_tokenized_%s.xlsx\" % (period, lang)\n",
    "\n",
    "# word cloud\n",
    "word_cloud_mask_path = \"data/plane.png\"\n",
    "word_cloud_file_path = \"out/word_cloud_%s_%s.png\" % (period, lang)\n",
    "\n",
    "# topic analysis\n",
    "feature_word_cnt = 500\n",
    "topic_cnt = 13\n",
    "topic_top_word_cnt = 25\n",
    "topic_analysis_res_path = \"out/lda_%d_%d.html\" % (feature_word_cnt, topic_cnt)\n",
    "lda_path = \"out/lda_%s_%s.mdl\" % (period, lang)\n",
    "feature_name_path = \"out/feature_name_%s_%s.mdl\" % (period, lang)\n",
    "\n",
    "# clustering\n",
    "cluster_cnt = 10\n",
    "kmeans_res_path = \"out/kmeans_%s_%d_%s.png\" % (period, cluster_cnt, lang)\n",
    "tendency_res_path = \"out/tendency_%s_%s.png\" % (period, lang)\n",
    "reduced_dimension = 2\n",
    "\n",
    "# classification\n",
    "kernel = \"poly\"\n",
    "clf_path = \"out/classifier_%s_%s.mdl\" % (period, lang)\n",
    "confusion_matrix_path = \"out/confusion_matrix_%s_%s_%s.png\" % (period, kernel, lang)\n",
    "\n",
    "data = get_from_file(weibo_data_path, twitter_data_path, processed_data_path, lang=lang)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "bd163fe2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>content</th>\n",
       "      <th>tokenized</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-02-24 06:48:02.000000</td>\n",
       "      <td>Ukraine MP Sophia Fedyna tells about the groun...</td>\n",
       "      <td>mp sophia fedyna tell ground situation convers...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022-02-24 06:48:02.000000</td>\n",
       "      <td>Footage of the airport bombing in Ivano-Franki...</td>\n",
       "      <td>footage airport russia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-02-24 06:48:03.000000</td>\n",
       "      <td>A cruise missile fired by the Russian army fel...</td>\n",
       "      <td>cruise missile army russia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-02-24 06:48:03.000000</td>\n",
       "      <td>🇺🇦 53rd Mechanized Brigade continues to suffer...</td>\n",
       "      <td>brigade loss area russia europe eu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-02-24 06:48:03.000000</td>\n",
       "      <td>SPREAD AND SHARE, YOU CAN HELP UKRAINE #Ukrain...</td>\n",
       "      <td>spread share help russia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3187</th>\n",
       "      <td>2022-04-30 00:00:12.000000</td>\n",
       "      <td>With Cries Of \"Christ is Risen\", Ukrainian Sol...</td>\n",
       "      <td>cry risen soldier rocket russiaukrainewar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3188</th>\n",
       "      <td>2022-04-30 00:00:12.000000</td>\n",
       "      <td>#Democrats: \"What do you mean by #MAGA? When w...</td>\n",
       "      <td>democrat maga biden regime politician voter co...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3189</th>\n",
       "      <td>2022-04-30 00:00:13.000000</td>\n",
       "      <td>Sunrise in Kyiv. Ukrainians made it thru the 6...</td>\n",
       "      <td>sunrise kyiv ukrainian night month putin claim...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3190</th>\n",
       "      <td>2022-04-30 00:00:14.000000</td>\n",
       "      <td>#SlavaUkraini🇺🇦🇺🇦🇺🇦🇺🇦🇺🇦🇺🇦🇺🇦Opinion: Expect Put...</td>\n",
       "      <td>slavaukraini🇺🇦🇺🇦🇺🇦🇺🇦🇺🇦🇺🇦🇺🇦opinion putin announ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3191</th>\n",
       "      <td>2022-04-30 00:00:15.000000</td>\n",
       "      <td>⚠️ Over the past few days, there have been no ...</td>\n",
       "      <td>day corridor civilian flee area reliefaid_nz b...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3192 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            time  \\\n",
       "0     2022-02-24 06:48:02.000000   \n",
       "1     2022-02-24 06:48:02.000000   \n",
       "2     2022-02-24 06:48:03.000000   \n",
       "3     2022-02-24 06:48:03.000000   \n",
       "4     2022-02-24 06:48:03.000000   \n",
       "...                          ...   \n",
       "3187  2022-04-30 00:00:12.000000   \n",
       "3188  2022-04-30 00:00:12.000000   \n",
       "3189  2022-04-30 00:00:13.000000   \n",
       "3190  2022-04-30 00:00:14.000000   \n",
       "3191  2022-04-30 00:00:15.000000   \n",
       "\n",
       "                                                content  \\\n",
       "0     Ukraine MP Sophia Fedyna tells about the groun...   \n",
       "1     Footage of the airport bombing in Ivano-Franki...   \n",
       "2     A cruise missile fired by the Russian army fel...   \n",
       "3     🇺🇦 53rd Mechanized Brigade continues to suffer...   \n",
       "4     SPREAD AND SHARE, YOU CAN HELP UKRAINE #Ukrain...   \n",
       "...                                                 ...   \n",
       "3187  With Cries Of \"Christ is Risen\", Ukrainian Sol...   \n",
       "3188  #Democrats: \"What do you mean by #MAGA? When w...   \n",
       "3189  Sunrise in Kyiv. Ukrainians made it thru the 6...   \n",
       "3190  #SlavaUkraini🇺🇦🇺🇦🇺🇦🇺🇦🇺🇦🇺🇦🇺🇦Opinion: Expect Put...   \n",
       "3191  ⚠️ Over the past few days, there have been no ...   \n",
       "\n",
       "                                              tokenized  \n",
       "0     mp sophia fedyna tell ground situation convers...  \n",
       "1                                footage airport russia  \n",
       "2                            cruise missile army russia  \n",
       "3                    brigade loss area russia europe eu  \n",
       "4                              spread share help russia  \n",
       "...                                                 ...  \n",
       "3187          cry risen soldier rocket russiaukrainewar  \n",
       "3188  democrat maga biden regime politician voter co...  \n",
       "3189  sunrise kyiv ukrainian night month putin claim...  \n",
       "3190  slavaukraini🇺🇦🇺🇦🇺🇦🇺🇦🇺🇦🇺🇦🇺🇦opinion putin announ...  \n",
       "3191  day corridor civilian flee area reliefaid_nz b...  \n",
       "\n",
       "[3192 rows x 3 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "94942ccf",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pyLDAvis\n",
    "import pyLDAvis.sklearn\n",
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "from sklearn.decomposition import LatentDirichletAllocation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "e0f6278d",
   "metadata": {},
   "outputs": [],
   "source": [
    "tf_vectorizer = CountVectorizer(strip_accents='unicode',\n",
    "                                    max_features=feature_word_cnt,\n",
    "                                    stop_words='english',\n",
    "                                    max_df=0.5,\n",
    "                                    min_df=10)\n",
    "tf = tf_vectorizer.fit_transform(data[\"tokenized\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "2011c503",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 307.14904617096164 -94953.45583274559\n",
      "2 313.78685732286823 -95307.92869452116\n",
      "3 316.47746087279535 -95449.48132871474\n",
      "4 324.8200408410484 -95880.85502330403\n",
      "5 328.22187459521086 -96053.58363575941\n",
      "6 332.478882951551 -96267.22927612675\n",
      "7 340.1085635749806 -96643.38230087863\n",
      "8 339.9378876139659 -96635.0604081252\n",
      "9 336.42594834148207 -96462.88986507877\n",
      "10 340.02398496986126 -96639.25890256606\n",
      "11 340.38456502678 -96656.83086671411\n",
      "12 340.35262010100286 -96655.27486261615\n",
      "13 343.71681162776315 -96818.34421901796\n",
      "14 345.7200157872547 -96914.68724538275\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plexs = []\n",
    "scores = []\n",
    "n_max_topics = 15\n",
    "for i in range(1,n_max_topics):\n",
    "    lda = LatentDirichletAllocation(n_components=i, max_iter=50,\n",
    "                                    learning_method='batch',\n",
    "                                    learning_offset=50,random_state=0)\n",
    "    lda.fit(tf)\n",
    "    plexs.append(lda.perplexity(tf))\n",
    "    scores.append(lda.score(tf))\n",
    "    print(i, plexs[-1], scores[-1])\n",
    "    # pic = pyLDAvis.sklearn.prepare(lda, tf, tf_vectorizer)\n",
    "    # topic_analysis_res_path = \"out/lda_%d_%d_%s.html\" % (feature_word_cnt, i, lang)\n",
    "    # pyLDAvis.save_html(pic, topic_analysis_res_path)\n",
    "    \n",
    "    \n",
    "n_t = n_max_topics - 1  # 区间最右侧的值。注意：不能大于n_max_topics\n",
    "x = list(range(1, n_t + 1))\n",
    "plt.plot(x, plexs[0:n_t])\n",
    "plt.xlabel(\"number of topics\")\n",
    "plt.ylabel(\"perplexity\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "7b828ed0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, scores[0:n_t])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ba930b66",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
